PROJECT SUMMARY The long-term objective of the PI's research program is to understand the molecular genetic mechanisms and driving forces of phenotypic variation and evolution. Pleiotropy is one of the most common yet least understood phenomena in genetics. It refers to the observation that one mutation impacts multiple phenotypic traits. Pleiotropy may be concordant or antagonistic, depending on whether the mutational effects on multiple traits are in the same or opposite directions (when the directions are alignable). Pleiotropy, especially antagonistic pleiotropy, is widely invoked in explanations and models of senescence, cancer, genetic disease, sexual conflict, cooperation, evolutionary constraint, adaptation, neofunctionalization, and speciation, among other things. This project addresses three key gaps in our understanding of pleiotropy: patterns, mechanisms, and evolutionary consequences. First, while the environmental pleiotropy of null mutations has been extensively studied, the same is not true for non-null mutations. This project will use a high-throughput method to determine the in vivo fitness landscapes of one yeast RNA gene and four protein genes in 12 environments. Each landscape will include >20,000 genotypes, providing unprecedentedly large data for inducing general principles of environmental pleiotropy. More importantly, these data will allow inferring fitness effects of mutations in one environment from those in another, which will be instrumental in explaining and predicting evolution in nature. Second, while pleiotropy is typically studied from the perspective of mutations, the other side of the coin is the relationship between phenotypic traits that are often impacted by the same mutations. Maximum growth rate r and carrying capacity K of density-dependent population growth are key life-history traits fundamental to many ecological and evolutionary theories and are directly relevant to combating pathogens and tumors. Although r and K are generally thought to be negatively correlated, both r-K tradeoffs and tradeups have been observed. However, neither the conditions under which each of these relationships occur nor the causes of these relationships are well understood. These questions will be addressed in yeast by mapping quantitative trait loci influencing r and K and estimating the r and K of 500 single-gene deletion strains in multiple environments, followed by modeling of biological processes impacting r and K. Third, if mutations with large benefits in one environment are generally deleterious in other environments, a population adapting to a changing environment may have few adaptive substitutions, despite continuous and strong selections. This project will test the above hypothesis using experimental evolution of yeast in constant vs. changing environments. If supported, this hypothesis will profoundly alter our interpretation of the nonsynonymous/synonymous substitution rate ratio estimated from intra and interspecific comparisons, impacting the assessment of the relative roles of genetic drift and positive selection in molecular evolution.